What does FictiveBox's IoT development service include?

The full stack from device to decision: edge and gateway firmware, time-series ingestion and storage at scale, digital twins, predictive maintenance models, device fleet management including provisioning and over-the-air updates, and industrial protocol integration.

When should a company bring in an IoT engineering partner?

Most often at the point where a pilot has to become production. An architecture that works on ten devices frequently fails at ten thousand, where ingestion cost, latency, over-the-air updates and fleet management become the real engineering problem. That transition is the phase we are built for.

What problems does industrial IoT engineering actually solve here?

It closes the gap between telemetry and action. Sensor data commonly sits in a historian while failures are still handled reactively. The work is turning that data into scored work orders inside the maintenance system operators already use, so the output is a job someone does rather than another dashboard.

How is an IoT engagement structured?

Four stages: Sense covers device and gateway instrumentation, Stream covers ingestion and storage, Reason covers models and digital twins, and Act pushes results into the operational systems where work happens. We work in two-week sprints with continuous delivery and production telemetry from the first sprint, so you are looking at real behaviour rather than a demo environment.

Which IoT technologies and protocols are supported?

MQTT, Kafka, Kubernetes, TimescaleDB, ClickHouse, Rust, Python, PyTorch, AWS IoT and Azure IoT Hub, together with industrial protocols such as OPC-UA and CAN on the edge side.

IoT Development Company

Industrial IoT from edge firmware to predictive intelligence.

We engineer the full IoT stack: low-power edge devices, secure gateways, ingestion at petabyte scale, digital twins and ML models that turn telemetry into work orders. We build for the phase after the pilot, when ten devices became ten thousand and the architecture that worked on a whiteboard stopped working in production.

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Capabilities

What we deliver

Edge and gateway firmware

C, C++ and Rust firmware for constrained MCUs, Linux gateways and RTOS. Certified industrial protocols, secure boot, signed OTA from day one.

Time-series at scale

Petabyte-class ingestion on Kafka, Pulsar, TimescaleDB, ClickHouse and S3 lakehouse patterns. Hot, warm and cold tiers designed for cost, not just performance.

Digital twins

Simulation-grade twins of fleets, plants and grids with bi-directional control loops. Built to drive decisions, not just visualize state.

Predictive maintenance

Anomaly detection, remaining useful life models and condition-based maintenance integrated directly into CMMS work orders.

Device fleet management

OTA updates, certificate rotation, secure boot and remote diagnostics across millions of devices. Security and uptime evidence for auditors.

Industrial protocols

OPC-UA, Modbus, MQTT, CAN, J1939, MVB and rail-specific TCN and Ethernet Train Backbone. We speak them without Googling them.

Outcomes

Why teams choose FictiveBox

412k events per second sustained ingestion on a single tenant

38% fewer unscheduled withdrawals on a 1,200-vehicle rail fleet

Sub-2-second end-to-end telemetry latency at 320M devices

+22% MTBF on substation transformer assets

Engagement

How we work

Step 01

Sense

Hardware selection, sensor placement and edge architecture. Designed around your physical environment, not a reference diagram.

Step 02

Stream

Resilient ingestion, schema governance and tiered storage. Cost and latency modeled before a single device goes live.

Step 03

Reason

Digital twins, ML models, alerting and operator dashboards wired to real workflows.

Step 04

Act

Closed-loop control, automated work order generation and measurable ROI you can show the CFO.

Products & Solutions

IoT Platforms We Build

Industrial IoT building blocks we deliver as accelerators on top of your fleet and physical infrastructure.

Stack

Tools & technologies

MQTTKafkaKubernetesTimescaleDBClickHouseRustPythonPyTorchAWS IoTAzure IoT Hub

FAQ

Common questions

What does FictiveBox's IoT development service include?: The full stack from device to decision: edge and gateway firmware, time-series ingestion and storage at scale, digital twins, predictive maintenance models, device fleet management including provisioning and over-the-air updates, and industrial protocol integration.
When should a company bring in an IoT engineering partner?: Most often at the point where a pilot has to become production. An architecture that works on ten devices frequently fails at ten thousand, where ingestion cost, latency, over-the-air updates and fleet management become the real engineering problem. That transition is the phase we are built for.
What problems does industrial IoT engineering actually solve here?: It closes the gap between telemetry and action. Sensor data commonly sits in a historian while failures are still handled reactively. The work is turning that data into scored work orders inside the maintenance system operators already use, so the output is a job someone does rather than another dashboard.
How is an IoT engagement structured?: Four stages: Sense covers device and gateway instrumentation, Stream covers ingestion and storage, Reason covers models and digital twins, and Act pushes results into the operational systems where work happens. We work in two-week sprints with continuous delivery and production telemetry from the first sprint, so you are looking at real behaviour rather than a demo environment.
Which IoT technologies and protocols are supported?: MQTT, Kafka, Kubernetes, TimescaleDB, ClickHouse, Rust, Python, PyTorch, AWS IoT and Azure IoT Hub, together with industrial protocols such as OPC-UA and CAN on the edge side.

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